1 Univariate distributions

1.1 Outcome: Rate difference per 100,000 person-days

rd_100k_pt_med rd_100k_pt_mean_wt rd_100k_25th rd_100k_75th
-0.059 0.179 -0.809 0.809

1.2 Intervention variables: Tree canopy and air conditioning

1.2.1 Tree canopy

tree_canopy_prop_min tree_canopy_prop_max tree_canopy_prop_mean tree_canopy_prop_med
0 0.708 0.108 0.061

1.2.2 Air conditioning

ac_prop_min ac_prop_max ac_prop_mean ac_prop_med
0 1 0.568 0.625

1.3 Other socio-demographic and geographic characteristics

1.3.1 Proportion above poverty

above_poverty_prop_min above_poverty_prop_max above_poverty_prop_mean above_poverty_prop_med
0.18 0.96 0.7 0.73

1.3.2 Proportion with insurance

insured_prop_min insured_prop_max insured_prop_mean insured_prop_med
0.58 1 0.9 0.91

1.3.3 Biome

biome_name area_km2
Temperate Conifer Forests 130,765
Deserts & Xeric Shrublands 118,685
Mediterranean Forests, Woodlands & Scrub 113,359
Temperate Grasslands, Savannas & Shrublands 46,273

1.3.4 Rural-urban classification

Definitions of rural-urban commuting codes:

  1. Metropolitan area core: primary flow within an urbanized area (UA)
  2. Metropolitan area high commuting: primary flow 30% or more to a UA
  3. Metropolitan area low commuting: primary flow 10% to 30% to a UA
  4. Micropolitan area core: primary flow within an Urban Cluster of 10,000 to 49,999 (large UC)
  5. Micropolitan high commuting: primary flow 30% or more to a large UC
  6. Micropolitan low commuting: primary flow 10% to 30% to a large UC
  7. Small town core: primary flow within an Urban Cluster of 2,500 to 9,999 (small UC)
  8. Small town high commuting: primary flow 30% or more to a small UC
  9. Small town low commuting: primary flow 10% to 30% to a small UC
  10. Rural areas: primary flow to a tract outside a UA or UC
ruca_cat pop area_km2
(0,3] 37,107,185 111,582
(3,6] 1,544,666 53,129
(6,9] 397,143 33,352
(9,10] 284,331 83,225

2 Bivariate and stratified associations

2.1 RD x Tree canopy x geographic measures

2.1.1 RD x Tree canopy

Here are scatterplots plotting the rate difference against the (square root of) proportion tree canopy.

There is a slight negative association between tree canopy and the RD, but it is rather weak.

Observations 1270
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.313 0.099 3.171 0.002
tree_canopy_prop_sqrt -0.839 0.295 -2.842 0.005
Standard errors: MLE
corr_spearman corr_pearson
-0.1 -0.09

2.1.2 RD x Tree canopy x biome

We stratified associations by biome, which illustrates, as above, that the tree-canopy distribution differs starkly by biome. The RD x tree canopy association appears to be negative in Mediterran Forests, Woodlands & Scrub and in Deserts & Xeric shrublands, but slightly positive in the other two.

Observations 1270
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.724 0.135 5.377 0.000
tree_canopy_prop_sqrt -1.700 0.438 -3.879 0.000
biome_name_freqTemperate Conifer Forests -1.443 0.633 -2.280 0.023
biome_name_freqTemperate Grasslands, Savannas & Shrublands -1.677 0.356 -4.716 0.000
biome_name_freqDeserts & Xeric Shrublands 0.415 0.477 0.869 0.385
tree_canopy_prop_sqrt:biome_name_freqTemperate Conifer Forests 2.634 1.099 2.397 0.017
tree_canopy_prop_sqrt:biome_name_freqTemperate Grasslands, Savannas & Shrublands 3.349 1.275 2.627 0.009
tree_canopy_prop_sqrt:biome_name_freqDeserts & Xeric Shrublands -5.139 2.978 -1.726 0.085
Standard errors: MLE
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub -0.17 -0.14
Temperate Conifer Forests -0.02 0.07
Temperate Grasslands, Savannas & Shrublands 0.23 0.16
Deserts & Xeric Shrublands -0.16 -0.16

2.1.3 RD x Tree canopy x rural-urban

We also stratified this association by urban-rural category.

The stratified scatterplot suggests that in the most urban areas and in the least urban areas, higher tree canopy is associated with a lower rate difference, whereas in the other two RUCA categories, the association is in the other direction: higher tree canopy is associated with a higher rate difference (i.e., suggesting a more harmful effect of wildfire on the outcome).

Observations 1270
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.518 0.121 4.291 0.000
tree_canopy_prop_sqrt -1.617 0.402 -4.024 0.000
ruca_cat(3,6] -0.817 0.337 -2.424 0.015
ruca_cat(6,9] -1.348 0.470 -2.866 0.004
ruca_cat(9,10] 0.816 0.485 1.683 0.093
tree_canopy_prop_sqrt:ruca_cat(3,6] 3.131 0.809 3.873 0.000
tree_canopy_prop_sqrt:ruca_cat(6,9] 2.702 1.274 2.120 0.034
tree_canopy_prop_sqrt:ruca_cat(9,10] -1.266 0.982 -1.290 0.197
Standard errors: MLE
ruca_cat corr_spearman corr_pearson
(0,3] -0.16 -0.14
(3,6] 0.26 0.16
(6,9] 0.09 0.10
(9,10] -0.18 -0.27

2.2 RD x A/C x geographic measures

2.2.1 RD x A/C

The association with air conditioning is weakly negative.

Observations 1104 (166 missing obs. deleted)
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.250 0.097 2.585 0.010
ac_prop -0.263 0.145 -1.811 0.070
Standard errors: MLE
overall corr_spearman corr_pearson
1 -0.11 -0.07

2.2.2 RD x A/C x biome

Observations 1104 (166 missing obs. deleted)
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.320 0.107 2.986 0.003
ac_prop -0.154 0.170 -0.904 0.366
biome_name_freqTemperate Conifer Forests -0.532 0.269 -1.980 0.048
biome_name_freqTemperate Grasslands, Savannas & Shrublands -1.312 0.559 -2.349 0.019
biome_name_freqDeserts & Xeric Shrublands 0.911 0.876 1.040 0.299
ac_prop:biome_name_freqTemperate Conifer Forests -0.097 0.605 -0.161 0.872
ac_prop:biome_name_freqTemperate Grasslands, Savannas & Shrublands 0.638 0.657 0.972 0.331
ac_prop:biome_name_freqDeserts & Xeric Shrublands -0.485 1.072 -0.453 0.651
Standard errors: MLE
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub -0.08 -0.05
Temperate Conifer Forests 0.05 -0.04
Temperate Grasslands, Savannas & Shrublands -0.01 0.10
Deserts & Xeric Shrublands -0.18 -0.06

2.2.3 RD x A/C x rural-urban

Like with tree canopy, the RD x A/C association varies by rural-urban category. It is more negative in more populous areas, and positive–suggesting air conditioning is associated with a higher difference effect of wildfire on acute-care utilization in less populous areas.

Observations 1104 (166 missing obs. deleted)
Dependent variable rd_100k_quo_pt
Type Linear regression
Est. S.E. t val. p
(Intercept) 0.346 0.105 3.283 0.001
ac_prop -0.388 0.157 -2.471 0.014
ruca_cat(3,6] 0.405 0.328 1.236 0.217
ruca_cat(6,9] -0.854 0.565 -1.511 0.131
ruca_cat(9,10] -2.005 0.420 -4.778 0.000
ac_prop:ruca_cat(3,6] -0.535 0.528 -1.013 0.311
ac_prop:ruca_cat(6,9] 0.394 0.783 0.503 0.615
ac_prop:ruca_cat(9,10] 3.374 0.653 5.165 0.000
Standard errors: MLE
ruca_cat corr_spearman corr_pearson
(0,3] -0.14 -0.10
(3,6] -0.18 -0.15
(6,9] -0.05 0.01
(9,10] 0.50 0.46

2.3 RD x community characteristics

2.3.1 RD x prop. above poverty

overall corr_spearman corr_pearson
1 -0.01 0.01

2.3.2 RD x prop. insured

The association between the RD and proportion with insurance is stronger than that between proportion above poverty.

overall corr_spearman corr_pearson
1 -0.06 -0.05

2.3.3 RD x biome

The RD distribution is in the positive direction in Mediterranean Forests, Woodlands & Scrub and more negative in all the others.

biome_name_freq n_zcta rd_100k_pt_med rd_100k_pt_mean_wt
Mediterranean Forests, Woodlands & Scrub 908 0.154 0.341
Temperate Conifer Forests 101 -0.282 0.043
Temperate Grasslands, Savannas & Shrublands 225 -0.498 -0.444
Deserts & Xeric Shrublands 62 -0.756 -0.534

2.3.4 RD x urban-rural category

The distribution is more negative in more rural areas, suggesting in those areas, wildfires had a preventive effect on healthcare utilization

ruca_cat n_zcta rd_100k_pt_med rd_100k_pt_mean_wt
(0,3] 1087 -0.033 0.196
(3,6] 99 -0.035 -0.164
(6,9] 51 -0.522 0.141
(9,10] 59 -0.732 -0.306

2.4 Tree canopy and AC x community characteristics

2.4.1 Tree canopy

2.4.1.1 Tree canopy x prop. above poverty

overall corr_spearman corr_pearson
1 0.34 0.26
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub 0.42 0.33
Temperate Conifer Forests 0.24 0.30
Temperate Grasslands, Savannas & Shrublands 0.31 0.32
Deserts & Xeric Shrublands 0.34 0.33

2.4.1.2 Tree canopy x prop. insured

overall corr_spearman corr_pearson
1 0.38 0.29
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub 0.45 0.36
Temperate Conifer Forests 0.10 0.15
Temperate Grasslands, Savannas & Shrublands 0.35 0.37
Deserts & Xeric Shrublands 0.15 0.18

2.4.1.3 Tree canopy x biome

2.4.1.4 Tree canopy x rural-urban

2.4.2 A/C

2.4.2.1 A/C x prop. above poverty

overall corr_spearman corr_pearson
1 0.03 0.01
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub 0.17 0.17
Temperate Conifer Forests -0.01 0.01
Temperate Grasslands, Savannas & Shrublands 0.41 0.38
Deserts & Xeric Shrublands 0.22 0.16

2.4.2.2 A/C x prop. insured

overall corr_spearman corr_pearson
1 0.04 0.09
biome_name_freq corr_spearman corr_pearson
Mediterranean Forests, Woodlands & Scrub 0.11 0.15
Temperate Conifer Forests -0.02 0.00
Temperate Grasslands, Savannas & Shrublands 0.31 0.32
Deserts & Xeric Shrublands 0.04 0.14

2.4.2.3 A/C x biome

2.4.2.4 A/C x rural-urban